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While Web 2.0 was about data, Web 3.0 is about knowledge and information. Scripting Intelligence: Web 3.0 Information Gathering and Processing offers the reader Ruby scripts for intelligent information management in a Web 3.0 environment—including information extraction from text, using Semantic Web technologies, information gathering (relational database metadata, web scraping, Wikipedia, Freebase), combining information from multiple sources, and strategies for publishing processed information. This book will be a valuable tool for anyone needing to gather, process, and publish web or database information across the modern web environment.
Text processing recipes, including speech tagging and automatic summarization
Gathering, visualizing, and publishing information from the Semantic Web
Information gathering from traditional sources such as relational databases and web sites
What you’ll learn
Gather and process information within the Web 3.0 environment.
See the flexibility of scripting with Ruby to gather and process information.
Extract text from various document formats.
Work with the Resource Description Framework (RDF) data model and SPARQL query language, the foundations of the Semantic Web.
Use GraphViz for data visualization.
Extract information from relational databases and web sites.
Who this book is for
Anyone needing to gather and display information available in electronic formats
Programmers needing to tag, summarize, or publish information
Ruby programmers and computer enthusiasts interested in seeing what Ruby can do with information management and Semantic Web tools
Academic researchers needing to extract and organize information in a more automated way
Table of Contents
1. Parsing Common Document Types
2. Cleaning, Segmenting, and Spell-Checking Text
3. Natural Language Processing
4. Using RDF and RDFS Data Formats
5. Delving Into RDF Data Stores
6. Performing SPARQL Queries and Understanding Reasoning
7. Implementing SPARQL Endpoint Web Portals
8. Working with Relational Databases
9. Supporting Indexing and Search
10. Using Web Scraping to Create Semantic Relations
11. Taking Advantage of Linked Data
12. Implementing Strategies for Large-Scale Data Storage
13. Creating Web Mashups
14. Performing Large-Scale Data Processing
15. Building Information Web Portals ISBN - 9788132200956
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Pages : 380
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